#include <iostream>
#include <vector>
#include "add_custom_tiling.h"
#include "register/op_def_registry.h"

// 假设的模拟 CANN 相关类和函数
namespace gert {
    class Shape {
    public:
        std::vector<size_t> shape;
        size_t GetShapeSize() const {
            size_t size = 1;
            for (auto dim : shape) {
                size *= dim;
            }
            return size;
        }
    };

    class TilingContext {
    public:
        const Shape* GetInputShape(int index) const {
            // 简单模拟，实际需要根据 CANN API 实现
            return &inputShape;
        }
        void SetBlockDim(uint32_t dim) {
            blockDim = dim;
        }
        struct RawTilingData {
            void* GetData() { return nullptr; }
            size_t GetCapacity() { return 0; }
            void SetDataSize(size_t size) {}
        };
        RawTilingData* GetRawTilingData() {
            return &rawTilingData;
        }
        size_t* GetWorkspaceSizes(int num) {
            static size_t workspaceSize = 0;
            return &workspaceSize;
        }
        Shape inputShape;
        uint32_t blockDim;
        RawTilingData rawTilingData;
    };

    class InferShapeContext {
    public:
        const Shape* GetInputShape(int index) const {
            return &inputShape;
        }
        Shape* GetOutputShape(int index) {
            return &outputShape;
        }
        Shape inputShape;
        Shape outputShape;
    };

    class InferDataTypeContext {
    public:
        int GetInputDataType(int index) const {
            return inputDataType;
        }
        void SetOutputDataType(int index, int dataType) {
            outputDataType = dataType;
        }
        int inputDataType;
        int outputDataType;
    };
}

namespace ge {
    enum DataType {
        DT_FLOAT16
    };
    enum Format {
        FORMAT_ND
    };
    enum ParamType {
        REQUIRED
    };
    class graphStatus {
    public:
        static const int GRAPH_SUCCESS = 0;
    };
}

// 模拟 TilingData 类的实现
class TilingData {
public:
    void set_totalLength(uint32_t length) {
        totalLength = length;
    }
    void set_tileNum(uint32_t num) {
        tileNum = num;
    }
    size_t GetDataSize() const {
        return sizeof(totalLength) + sizeof(tileNum);
    }
    void SaveToBuffer(void* buffer, size_t capacity) const {
        // 简单模拟，实际需要将数据保存到 buffer
    }
private:
    uint32_t totalLength;
    uint32_t tileNum;
};

// 模拟 OpDef 类和 OP_ADD 宏
class OpDef {
public:
    OpDef(const char* name) {}
    struct InputParam {
        std::string name;
        ge::ParamType paramType;
        std::vector<ge::DataType> dataTypes;
        std::vector<ge::Format> formats;
    };
    struct OutputParam {
        std::string name;
        ge::ParamType paramType;
        std::vector<ge::DataType> dataTypes;
        std::vector<ge::Format> formats;
    };
    OpDef& Input(const std::string& name) {
        inputParams.push_back({name, ge::REQUIRED, {ge::DT_FLOAT16}, {ge::FORMAT_ND}});
        return *this;
    }
    OpDef& Output(const std::string& name) {
        outputParams.push_back({name, ge::REQUIRED, {ge::DT_FLOAT16}, {ge::FORMAT_ND}});
        return *this;
    }
    OpDef& ParamType(ge::ParamType type) {
        if (!inputParams.empty()) {
            inputParams.back().paramType = type;
        }
        return *this;
    }
    OpDef& DataType(const std::vector<ge::DataType>& types) {
        if (!inputParams.empty()) {
            inputParams.back().dataTypes = types;
        }
        if (!outputParams.empty()) {
            outputParams.back().dataTypes = types;
        }
        return *this;
    }
    OpDef& Format(const std::vector<ge::Format>& formats) {
        if (!inputParams.empty()) {
            inputParams.back().formats = formats;
        }
        if (!outputParams.empty()) {
            outputParams.back().formats = formats;
        }
        return *this;
    }
    OpDef& SetInferShape(ge::graphStatus (*func)(gert::InferShapeContext*)) {
        inferShapeFunc = func;
        return *this;
    }
    OpDef& SetInferDataType(ge::graphStatus (*func)(gert::InferDataTypeContext*)) {
        inferDataTypeFunc = func;
        return *this;
    }
    struct AICoreConfig {
        ge::graphStatus (*tilingFunc)(gert::TilingContext*);
        std::vector<std::string> chipConfigs;
    };
    AICoreConfig& AICore() {
        return aiCoreConfig;
    }
    AICoreConfig& SetTiling(ge::graphStatus (*func)(gert::TilingContext*)) {
        aiCoreConfig.tilingFunc = func;
        return aiCoreConfig;
    }
    AICoreConfig& AddConfig(const std::string& config) {
        aiCoreConfig.chipConfigs.push_back(config);
        return aiCoreConfig;
    }
    std::vector<InputParam> inputParams;
    std::vector<OutputParam> outputParams;
    ge::graphStatus (*inferShapeFunc)(gert::InferShapeContext*);
    ge::graphStatus (*inferDataTypeFunc)(gert::InferDataTypeContext*);
    AICoreConfig aiCoreConfig;
};

#define OP_ADD(OpClass) \
    static OpClass op##OpClass(#OpClass);

// 引入之前的 add_custom.cpp 中的代码
#include "add_custom.cpp"

// 模拟的张量数据类
class Tensor {
public:
    std::vector<float> data;
    gert::Shape shape;
    Tensor(const std::vector<float>& d, const gert::Shape& s) : data(d), shape(s) {}
};

// 模拟的加法算子执行函数
Tensor add_custom_operator(const Tensor& x, const Tensor& y) {
    std::vector<float> result;
    for (size_t i = 0; i < x.data.size(); ++i) {
        result.push_back(x.data[i] + y.data[i]);
    }
    return Tensor(result, x.shape);
}

int main() {
    // 测试 TilingFunc
    gert::TilingContext tilingContext;
    tilingContext.inputShape.shape = {2, 3};
    ge::graphStatus tilingStatus = optiling::TilingFunc(&tilingContext);
    if (tilingStatus == ge::graphStatus::GRAPH_SUCCESS) {
        std::cout << "TilingFunc executed successfully. BlockDim: " << tilingContext.blockDim << std::endl;
    } else {
        std::cout << "TilingFunc failed." << std::endl;
    }

    // 测试 InferShape
    gert::InferShapeContext inferShapeContext;
    inferShapeContext.inputShape.shape = {4, 5};
    ge::graphStatus inferShapeStatus = ge::InferShape(&inferShapeContext);
    if (inferShapeStatus == ge::graphStatus::GRAPH_SUCCESS) {
        std::cout << "InferShape executed successfully. Output shape size: "
                  << inferShapeContext.outputShape.GetShapeSize() << std::endl;
    } else {
        std::cout << "InferShape failed." << std::endl;
    }

    // 测试 InferDataType
    gert::InferDataTypeContext inferDataTypeContext;
    inferDataTypeContext.inputDataType = ge::DT_FLOAT16;
    ge::graphStatus inferDataTypeStatus = ge::InferDataType(&inferDataTypeContext);
    if (inferDataTypeStatus == ge::graphStatus::GRAPH_SUCCESS) {
        std::cout << "InferDataType executed successfully. Output data type: "
                  << inferDataTypeContext.outputDataType << std::endl;
    } else {
        std::cout << "InferDataType failed." << std::endl;
    }

    // 测试加法算子
    gert::Shape inputShape = {{2, 2}};
    std::vector<float> inputDataX = {1.0, 2.0, 3.0, 4.0};
    std::vector<float> inputDataY = {5.0, 6.0, 7.0, 8.0};
    Tensor x(inputDataX, inputShape);
    Tensor y(inputDataY, inputShape);

    Tensor result = add_custom_operator(x, y);

    std::cout << "AddCustom operator test result:" << std::endl;
    for (float val : result.data) {
        std::cout << val << " ";
    }
    std::cout << std::endl;

    return 0;
}    